Current GPS receivers and operating methods seek to acquire the GPS signals transmitted from a constellation of satellites so as to perform pseudorange calculations in order to determine the respective distances from the receiver to each of the satellites. The acquisition of the GPS signals is achieved by means of energy detection at the output of the received, and despread, signal and this approach involves the tuning of a code signal generated locally by the receiver but taking account of possible phase and frequency offsets which are anticipated as likely by the receiver. When the phase of the despread signal and the local generated code signal are within the specified limits, the detector then produces an output which exceeds some threshold value and the receiver can then register the presence of the desired signal. This initial acquisition of the signal then triggers verification and tracking steps which attempt to continuously maintain close alignment between the two code sequences in order to track any incoming signal fluctuation. If the signal phase and frequency offsets are not within the desired limits, the output of the detector will fail to reach the threshold value and so the search for initial acquisitions will continue.
Because of the Doppler effect that can be introduced into the incoming signals due to relative motion between the receiver and the satellite, it is anticipated that the incoming GPS satellite signals can be represented within a broad range of frequencies.
A GPS receiver commonly employs a plurality of search bins the number of which is determined by the number of possible code phase offsets and the total range of possible Doppler offsets.
Current GPS implementations do not allow GPS reception in areas of significant GPS signal attenuation such as in so-called urban canyons or indoor locations. While current receivers integrate for a maximum of 1 ms it is appreciated that, the longer the integration time, the greater the sensitivity that can be achieved. With very long integration periods, it would be possible to receive GPS signals in extremely harsh signal environments such as indoors.
It is appreciated that there is a combined sensitivity/acquisition time trade-off for GPS receivers. Although sensitivity can be readily improved, this has an adverse effect on acquisition time. With current implementations involving serial searches, this proves problematic because there is a non-linear relationship between sensitivity and acquisition time. For example, it has previously been noted that processing gain is achieved by reducing the noise variance of the integrated power. This can be achieved either coherently and/or non-coherently. The gain and search time as a function of non-coherent power sums N, and the coherent pre-detection interval (PDI) in milliseconds, can be represented as:Processing gain=10 log [PDI√{square root over (N)}] dB.Search time increases=the PDI (due to increased PDI)×the PDI (due to frequency step reduction)×N (number of non-coherent sums)=N×(PDI)2.
It should be appreciated that the non-coherent case comprises the non-coherent summing of more than one chunk, where each chunk is itself summed coherently.
For a 100 ms search time therefore with coherent PDI=10 ms and 10 non-coherent sums, the processing gain is 15 dB but the search time increases by a factor of 1000.
Acquisition time then becomes problematic since if 15 dB gain is required to detect the signal, the acquisition time goes up from in the region of 1 second to over half an hour.
What would therefore be advantageous is a long integration technique so as to enable high sensitivity but which would not severely impact computation, and thus acquisition, time. It would also be valuable to have a technique that will prove effective without requiring assistance messaging.
It is known from WO-A-99/26370 to seek to reduce the said acquisition time by searching for all possible Doppler codes simultaneously by the employment of a Fast Fourier Transform (FFT) as part of the acquisition system. This document discloses the use of an FFT combiner which is thought advantageous in that it enables a broad range of frequencies which might contain GPS signals to be searched simultaneously thereby reducing the time required to achieve signal fix. Without employing such an FFT combiner, the range of frequencies that can be searched simultaneously is disadvantageously limited and multiple searches must then be carried out which disadvantageously exhibit time delays.
However, such known FFT combiners nevertheless exhibit disadvantages in that they experience so-called scalloping losses between each of the bins.
In further detail, the FFT combiner such as that of WO-A-99/26370 uses a FFT to estimate the correct Doppler. The FFT is a complex-valued transform and the K-point FFT of a sampled signal x(kTs) of length K is
      X    ⁢          (      l      )        =            ∑              k        =        0                    K        -        1              ⁢                  ⁢                  x        ⁢                  (                      kT            s                    )                    ⁢              ⅇ                              -            j2                    ⁢                                          ⁢          π          ⁢                      kl            K                              
The value of I for which the magnitude of X(I) is maximum indicates the strongest frequency component in x(kTs). Most signal processing texts discuss FFTs with some detail and FFTs are amenable to numerous efficient hardware or software implementations and can be employed in the context of code correlation.
The known FFT combiner technique functions as follows. First, a “chunk size” of N samples is defined e.g. N=4800 corresponds to 1 ms chunks in a receiver set up using 4.8 MHz sampling frequency. Correlation with a satellite PN code of interest is carried out and after integration for the N samples, the result is stored. This is repeated for K consecutive sets of N samples, so that KN samples in total are processed. The FFT of the K integration results is then obtained and if the satellite signal is present, a peak is clearly visible. If this is true then the FFT bin corresponding to this peak will correspond to the Doppler shift of the signal.
The whole procedure is represented diagrammatically in FIG. 2 using a “serial” approach, i.e. the integration results are obtained sequentially. A parallel implementation is also possible for matched filter approaches, as is described in WO-A-99/26370 where the matched filter is divided into K subsections and integration results from each “partial” matched filter are subjected to the FFT.
In comparison to a standard serial search, the proposal in effect searches K Doppler bins simultaneously using the FFT Combiner and hence exhibits a relatively short time-to-first-fix. This difference is clear from FIG. 3 where it can be seen that the FFT combiner appears nearly equivalent to K separate Doppler serial searches centred, in this example, every 1 kHz.
However, it is noted that the FFT combiner incurs a sensitivity loss of up to −4 dB; a so-called scalloping loss, at various values of Doppler error when the integration time increases beyond 1 ms, as can be seen from FIG. 4.